Technologies for increased auto safety—through tailored, intelligent restraint systems or better ways to alert drivers to dangers—are the aims of labs at the University of Michigan and the University of Minnesota.

The HumanFIRST laboratory at the University of Minnesota is working on ways to prevent automobile accidents caused by cars swerving out of their lanes. This sort of accident, which often occurs on rural roads, accounts for one third of all crashes and as many as 55 percent of all traffic fatalities.

The key factor in many of these accidents is human error: speeding, alcohol, fatigue, or driver distraction. According to Christopher Edwards, a research fellow at the HumanFIRST lab, Minnesota’s Local Road Research Board is funding studies of lane departure warning systems to determine their potential effectiveness in assisting drivers. Some systems use stereo visual reckoning to determine when the car has crossed the lane line. Other systems in development use global positioning satellites reckoning against a digital map. When a system determines that a car has drifted out of lane, it warns the driver to make a correction.

HumanFIRST has investigated a number of methods to alert drivers to a number of critical situations, such as a voice or visual alert, but studies have suggested that physical stimulation might result in faster driver responses, especially for lane departures.

The portable driving environment simulator. Image: HumanFIRST

One option, investigated by HumanFIRST and previous research, was a quick but non-steering jerk of the wheel, but that created an uncomfortable sense that the car wanted control and resulted in overcompensation by drivers.

Sometimes, the strongest message is an old-fashioned kick in the pants. The lab equipped a simulator with physical actuators on the right and left sides of the seat. They would vibrate each time the simulated car departed the right or left side of the marked lane. This would give the driver immediate feedback not only of lane drift, but also of the direction of error.

The lab ran tests with 60 drivers from the ages of 21 to 65. The scenario simulated wind gusts pushing a car out of lane.

According to Edwards, subjects were assigned to reliability groups and analysis comparisons were conducted between groups. Each subject took a simulated drive during which no warning was given, and the results served as a baseline. Then each driver took four more simulated drives with 12 simulated wind gusts per drive. The curves and straightaways differed on each simulated course.

It turns out the system can be too sensitive. Based on records of driver responses, 100 percent sensitivity—buzzing every time the wheel touches the center line—was less effective than setting the system to be a little more forgiving.

When the system sent a warning for 90 percent of lane drift infractions, or even for 70 percent, driver response times were faster. There were also fewer instances of significant lane drift.

Also, drivers—regardless of the condition or the curve of the roadway—did not significantly slow down during lane drift. This reflects the driver training mantra to steer back safely onto the roadway, but suggests additional questions regarding the same behavior for curves and straight sections, Edwards said.

The results supported the findings of previous research in at least one way: A perfectly reliable system may make drivers complacent.